VS Code / Python

Setting Up the Developer Environment

1. Introduction to the Python Ecosystem

• Understanding virtual environments
• Exploring Python's "batteries included" philosophy

2. Tools for Interactive Workflow

• A dive into Jupyter notebooks

3. Integrated Development Environment (IDE)

• Introduction to VS Code and Git
• VS Code setup: Essential plugins and optimal settings

Hands-on Project - Data Pipeline: Ingest, Transform, Load & Visualize

This project aims to teach crucial Python skills and relevant libraries in a client-focused domain. It will cover:

1. Data Ingestion

• Importing data from Morningstar

2. Exploratory Data Analysis (EDA) and Data Wrangling

• Utilizing NumPy, Pandas, Seaborn, and Plotly
• Performing data profiling

3. Data Transformation

• Converting data into suitable target structures

4. Version Control

• Managing source code with Git

Key Technologies Covered:

1. NumPy

• Comparing Python lists vs. NumPy arrays and matrices
• Understanding universal functions, slicing, broadcasting, and boolean indexing

2. Pandas

• Data exploration and I/O (focus on CSV/XLSX and database communication)
• Advanced data processing: aggregations, pivot tables, data distributions, manipulations, joining/splitting datasets
• Working with time-series data

3. Data Visualization

• Creating visualizations using Matplotlib, Seaborn, and Plotly Express
• Some pointers to dashboarding

4. VS Code in Practice

• Applying VS Code to script-based and interactive workflows
• Data wrangling techniques
• Integrating with Git, Python, and data sources
• Customizing VS Code for specific workflows